Risky business: factor analysis of survey data – assessing the probability of incorrect dimensionalisation

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations.We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of overdimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems

Measurement invariance of the center for epidemiological studies depression scale (CES-D) among chinese and dutch elderly

Background: Although previous studies using non- elderly groups have assessed the factorial invariance of the Center for Epidemiological Studies Depression Scale (CES-D) across different groups with the same social-cultural backgrounds, few studies have tested the factorial invariance of the CES-D across two elderly groups from countries with different social cultures. The purposes of this study were to examine the factorial structure of the CES-D, and test its measurement invariance across two different national elderly populations. Methods. A total of 6806 elderly adults from China (n = 4903) and the Netherlands (n = 1903) were included in the final sample. The CES-D was assessed in both samples. Three strategies were used in the data analysis procedure. First, a confirmatory factor analysis (CFA) was carried out to determine the factor structures of the CES-D that best fitted the two samples. Second, the best fitting model was incorporated into a multi-group CFA model to test measurement invariance of the CES-D across the two population groups. Third, latent mean differences between the two groups were tested. Results: The results of confirmatory factor analysis (CFA) showed: 1) in both samples, Radloff's four-factor model resulted in a significantly better fit and the four dimensions (somatic complaints, depressed affect, positive affect, and interpersonal problems) of the CES-D seem to be the most informative in assessing depressive symptoms compared to the single-, three-, and the second-order factor models; and 2) the factorial structure was invariant across the populations under study. However, only partial scalar and uniqueness invariance of the CES-D items was supported. Latent means in the partial invariant model were lower for the Dutch sample, compared to the Chinese sample. Conclusions: Our findings provide evidence of a valid factorial structure of the CES-D that could be applied to elderly populations from both China and the Netherlands, producing a meaningful comparison of total scores between the two elderly groups. However, for some specific factors and items, caution is required when comparing the depressive symptoms between Chinese and Dutch elderly groups. © 2011 Zhang et al; licensee BioMed Central Ltd

Evaluation of nature conservation - An application to the Dutch Ecological Network

Recent literature shows a lively debate on how to capture ecological and environmental aspects in different evaluation methods and the closely related issue of the (im)possibilities of monetization of these aspects. Although economists in general tend to favour Cost-Benefit Analysis (CBA) above Multi-Criteria Analysis (MCA), part of the literature suggests that CBA falls short of being the only decision-making device for environmental problems, both for theoretical and practical reasons. This paper discusses both evaluation methods and the main results of a major, publicly-financed nature conservation project in The Netherlands. The evaluation method combines the straightforwardness of CBA with the flexibility of MCA. Conceptually, it consists of a MCA, the net result of a CBA being integrated as one of the criteria. The different aspects of the nature conservation project that can be monetized are incorporated into the CBA. Other aspects such as changes in biodiversity or scenic beauty are analysed in their own dimension, provided (cardinal) quantification is possible. In fact, the analysis consists of a very simple MCA, with two criteria: social costs and a quantitative measure of nature. Quantifying the amount of nature in its own, non-monetary dimension is a key element of the empirical analysis. A detailed quantitative estimate is made of the improvement of nature, based upon 564 species and 131 different ecosystems. The result of the evaluation is a trade-off at the national level between ecological improvements (plus 18 percent) and social costs (DFl. 3.4 billion net present value). Due to the detailed quantification of the effect on nature the evaluation also yields results about the cost-effectiveness of four different instruments to create and to preserve nature. That part of the analysis shows that complete withdrawal of agricultural land for nature purposes in the project in general is more cost-effective than subsidizing nature-friendly farming, although the former is more expensive

Relating land-use intensity and biodiversity at the regional scale

Changes in biodiversity are often attributed to economically driven land-use changes, but the relation is not too well documented. Land-use changes involve both changes to a different function and shifts in intensity within a function. The relation between land-use changes and biodiversity changes at the meso-level. in the province of Drenthe is the object of study of the present paper. Commonly available indicators about land-use and biodiversity appear to be related to each other in complicated ways. The biodiversity parameters that react most unambiguously to changing Land-use are plant functional types. The clearest relation is found when changes to a different function occur. (c) 2005 Elsevier GmbH. All rights reserved